Presently, network-accessible computing services sometimes referred to as cloud computing services or remote computing services, offer flexibly to customers in their computing choices. When customers instantiate new virtual machine instances within a computer resource service or migrate instances to the computer resource service, the customers may evaluate the resource characteristics of the instance executing in the computer resource service. This can include, among other possibilities, processor type and performance, memory size and performance, input/output capabilities, ephemeral storage size, and network capabilities.
Each instance type can have a different performance profile providing a degree of choice to the customer. However, it can be difficult to select between different instance types in terms of performance at a given time and location (e.g. a particular datacenter) due to various inconsistencies. For example, the instances may be hosted on differing underlying physical hardware, which may alter the actual performance of the instances (e.g. older hardware may perform differently than newer hardware). Also, instances, which are implemented in “busy” locations in the computer resource service (e.g. noisy neighbors), may provide reduced performance than in a less-subscribed area. Accordingly, it can be challenging to understand the performance profile of the instances in the computer resource service.